1. Field of the Invention
The present invention relates to encoded information, and more specifically, to recognition of encoded information on documents.
2. Description of Related Art
Various technologies are available for recognizing information encoded or written on documents, such as checks, deposit slips, surveys, tests, and the like. Examples of such information recognition technologies include magnetic ink character recognition (MICR) and optical mark recognition (OMR).
MICR allows computers to read information or characters from printed documents. MICR is commonly used by the banking industry or retailers to facilitate the processing of checks or other documents such as deposit slips. MICR characters are printed in special typefaces with a magnetic ink or toner, usually containing iron oxide. As a machine decodes the MICR text, it first magnetizes the characters in the plane of the paper. Subsequently, the characters or key data are passed over a MICR read head. As each character passes over the MICR read head, it produces a unique waveform that can be identified by the MICR system.
The quality and types of documents containing encoded information can vary widely. For example, MICR character signal strength can range more than seven times from one check to another. Such variances can complicate accurate character recognition. In the example of signal strength variations, low signal strength checks have signal amplitude close to the noise level, and the noise amplitude can interfere with proper character recognition. On the other hand, high signal strength checks can cause clipping in an analog amplifier circuit of the MICR system, which may cause erroneous character recognition. Another difficulty encountered with MICR character recognition can occur when checks or other documents are printed by laser printers, which can cause incorrect recognition results because individual rows of dots can appear as several smaller peaks rather than fewer larger peaks. Use of OMR technology may also be prone to erroneous recognition results for similar reasons. In view of these difficulties, there is a need for improved MICR character recognition and for improved recognition of encoded information on documents in general.